A commodity search system for online shopping based on ontology and web mining

With the popularity of Internet and e-commerce, the number of shopping websites has rapidly increased on the Internet, and this enables people to shop easily through the Internet. Consumers spend a lot of time searching commodity, because they need to filter and compare search results data by themselves. In recent years, there is a growing parity websites helping consumers to buy cheaper commodity. Although these websites can help consumers get the parity price of commodities, the search results are not so ideal. Because these websites may occur problems about the difference commodity between search results and consumers want to search, or the difference commodity price between search results and commodity web page. Therefore, this study attempts to use semantic analysis, ontology, and web mining technique as a basic approach. This study proposes a novel commodity search system to track consumer demand, and that is, when the commodity price of any website is lower than the consumer price conditions, the system will proactively notify consumers. This study results indicate that the novel commodity search system could assist consumers to search commodity, and provide historical price information of commodity for consumers to decide.